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--- public:t-malv-15-3:4 [2015/09/10 22:34] – [5. Working with Bigram scores] orvark
+++ public:t-malv-15-3:4 [2024/04/29 13:33] (current) – external edit 127.0.0.1
@@ Line 95: / Line 95: @@
 FYI: a normal Python dictionary throws a ''KeyError'' if you try to get an item with a key that is not currently in the dictionary. The ''defaultdict'' in contrast will simply create any items that you try to access if they don't exist. See [[http://www.nltk.org/book/ch05.html|section 3.4 in chapter 5 in the NLTK book]].
+===== Solutions  =====
+<code python>
+import nltk
+from nltk.collocations import *
+from nltk.metrics import BigramAssocMeasures, TrigramAssocMeasures, spearman_correlation, ranks_from_scores
+from nltk.corpus import brown, stopwords
+#1
+bam = BigramAssocMeasures
+corpus =  brown.words()  # ok to use a subset e.g. 'ca01' for testing
+finder = BigramCollocationFinder.from_words(corpus)
+word_filter = lambda w: len(w) < 3 or w.lower() in stopwords.words('english')
+#def word_filter(w): return len(w) < 3 or w.lower() in stopwords.words('english')
+finder.apply_freq_filter(2)
+finder.apply_word_filter(word_filter)
+print(finder.nbest(bam.raw_freq, 20))
+finder_win3 = BigramCollocationFinder.from_words(corpus, window_size=3)
+finder_win3.apply_freq_filter(2)
+finder_win3.apply_word_filter(word_filter)
+print(finder_win3.nbest(bam.raw_freq, 20))
+tam = TrigramAssocMeasures
+finder_tri = TrigramCollocationFinder.from_words(corpus)
+finder_tri.apply_freq_filter(2)
+finder_tri.apply_word_filter(word_filter)
+print(finder_tri.nbest(tam.raw_freq, 20))
+#2
+# Pointwise mutal information
+print(finder.nbest(bam.pmi, 20))
+# Log-likelihood ratio
+print(finder.nbest(bam.likelihood_ratio, 20))
+# Mutal information likelihood, a mi variant
+print(finder.nbest(bam.mi_like, 20))
+# Chi squared test
+print(finder.nbest(bam.chi_sq, 20))
+# Student's t-test, w/independence hypothesis for unigrams
+print(finder.nbest(bam.student_t, 20))
+#3
+tagged_corpus = brown.tagged_words(tagset='universal')  # ok to use a subset e.g. 'ca01' for testing
+finder_tagged = BigramCollocationFinder.from_words(tagged_corpus)
+print(finder_tagged.nbest(bam.raw_freq, 20))
+finder_tags = BigramCollocationFinder.from_words(t for w, t in tagged_corpus)
+print(finder_tags.nbest(bam.raw_freq, 20))
+</code>